Six Sigma: A Case Study Approach Using Minitab®

✍ Scribed by Timothy D. Blackburn

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 268
• Edition: 1st ed. 2022
• Category: Library

✦ Synopsis

This book introduces the reader to Six Sigma, a problem-solving technique for reducing defects and variation in processes. The author uses DMAIC phases (Define, Measure, Analyze, Improve and Control) and a data-centric approach, leveraging applied statistics with Minitab^®. Readers are enabled to solve novel problems where there isn’t an apparent root cause or solution identified. The author walks readers through an (imaginary) case study, explaining both the DMAIC approach and how to use Minitab in a practical way. The presentation includes data sets and instructions on how to analyze data in the context of Six Sigma using Minitab.

✦ Table of Contents

Preface
Acknowledgments
Contents
Acronymns
About the Author
1: The Case Study – KIND Karz
References
2: An Introduction to Six Sigma
References
3: The Define Phase
3.1 Project Charter
3.2 Voice of the Customer (VOC) and Critical to Quality (CTQ) Hierarchy
3.3 SIPOC and Mapping
3.4 Stakeholder Analysis
3.5 Learnings from Similar Incidences
3.6 Other Background Information and Contents
References
4: The Measure Phase (with Minitab Tools)
4.1 The Measure Phase: An Overview
4.1.1 Data Collection
4.1.2 Process Stability
4.1.3 Process Capability
4.1.4 Measurement System Analysis (MSA)
4.1.5 Funneling and Stratification
4.2 Control Charts: Minitab Methods and Analysis Detail
4.2.1 Common Cause Versus Special Cause Variation
4.2.2 Control Chart Fundamentals
4.2.3 The Individual Moving Range Control Chart in Minitab
4.2.4 The P-Chart for Proportional Data in Minitab
4.2.5 The X-Bar R Chart for Systematically Sampled Data in Minitab
4.2.6 Control Chart for Attributes: The U-Chart in Minitab
4.2.7 Assessing Unusual Patterns: The Run Chart in Minitab
4.3 Capability Analysis: Minitab Methods and Analysis Detail
4.3.1 Introduction to Capability Analysis
4.3.2 Using Minitab to Calculate Ppk for Continuous Data
4.3.3 Using Minitab to Calculate Ppk for Continuous Data: Non-normal
4.3.4 Discrete Data Process Capability
4.3.5 Calculating Ppk for Discrete Data in Minitab
4.4 Measurement System Analysis (with Gage R&R, Attribute Agreement Analysis): Minitab Methods and Analysis Detail
4.4.1 Introduction to Gage R&R and Attribute Agreement Analysis
4.4.2 GAGE R&R: Overview
4.4.3 Designing and Analyzing the GAGE R&R Study in Minitab
4.4.4 Attribute Agreement Analysis in Minitab
4.5 Pareto Analysis: Minitab Methods and Analysis Detail
4.5.1 Creating a Pareto Chart
4.5.2 Constructing a Pareto Chart in Minitab
4.6 Test of Proportions: Minitab Methods and Analysis Detail
4.6.1 Introduction to Test of Proportions
4.6.2 Test of Two Proportions in Minitab
4.6.3 Chi-Square Test of Multiple Proportions in Minitab
References
5: The Analyze Phase with Minitab Tools
5.1 The Analyze Phase: An Overview
5.1.1 Introduction
5.1.2 Cause and Effect Analysis
5.1.3 Verifying or Discarding Root Causes: Process Analysis
5.1.4 Verifying or Discarding Root Causes: Data Analysis
5.1.5 Piloting
5.1.6 Data Analysis Example: Regression
5.1.7 Data Analysis Example: Two Sample T Test
5.1.8 Data Analysis Example: Paired T Test
5.1.9 Data Analysis Example: ANOVA, ANOM
5.1.10 Data Analysis Example: Design of Experiment (DOE)
5.1.11 Summary Root Cause Tables
5.2 Regression Analysis: Minitab Methods and Analysis Detail
5.2.1 Regression Overview
5.2.2 Assumptions for Linear Regression and Key Data Interpretations
5.2.3 Single Linear Regression
5.2.4 Multiple Linear Regression
5.2.5 Regression Issues
5.2.6 Correlation and Visualization in Minitab
5.2.7 Other Regression Tools (Introduction)
5.3 Two Sample T Test, Mann-Whitney: Minitab Methods and Analysis Detail
5.3.1 Two Sample T Test Overview
5.3.2 Two Sample T Test in Minitab
5.3.3 Mann-Whitney Test in Minitab
5.3.4 Data Transformations in Minitab
5.3.5 Sample Size Determination in Minitab
5.4 Paired T Test: Minitab Methods and Analysis Detail
5.4.1 Paired T Test Overview
5.4.2 Paired T Test in Minitab
5.4.3 One Sample Wilcoxon in Minitab (Nonparametric Alternative to a Paired T Test)
5.5 ANOVA, ANOM: Minitab Methods and Analysis Detail
5.5.1 ANOVA and ANOM Overview
5.5.2 ANOVA in Minitab
5.5.3 ANOM in Minitab
5.5.4 Kruskal-Wallis in Minitab (Nonparametric Alternative to ANOVA)
5.6 Design of Experiment: Minitab Analysis and Methods Detail
5.6.1 DOE Overview
5.6.2 Full Factorial DOE Example in Minitab (No Interactions Between X’s)
5.6.3 Full Factorial DOE Example in Minitab (with Interactions)
5.6.4 Introduction to Screening Designs and Reduced Factorials
5.6.5 Other DOE Concepts and Methods
References
6: The Improve Phase
6.1 Introduction
6.2 Implementation Plans
6.3 Arriving at Solutions
6.4 Cost-Benefit Analysis
6.5 Risk Analysis
6.6 Piloting
References
7: The Control Phase
7.1 Introduction
7.2 Confirming Objectives Were Achieved
7.3 Monitoring and Control Strategy
7.4 Standardization
7.5 Project Closure and Hand-off
References
8: Storyboards
8.1 Define Phase Storyboard Recommended Contents
8.2 Measure Phase Storyboard Recommended Contents
8.3 Analyze Phase Storyboard Recommended Contents
8.4 Improve Phase Storyboard Recommended Contents
8.5 Control Phase Storyboard Recommended Contents
Appendixes
Appendix A: Introduction to Minitab V19–21
Appendix B: Datasets
Epilogue
References
Index